In the not-so-distant future, a 66-year-old man is drinking his morning tea when he suddenly feels his face go numb. His teacup spills to the floor as the hand that was holding it falls limp by his side. His wife enters the room and seems upset, but the man has difficulty understanding what she is saying. He has a pounding headache.
This man may have just had a stroke—a blockage or break in a blood vessel in the brain. If so, the treatment he receives in the next four hours could mean the difference between whether he lives or dies—whether he recovers fully or becomes permanently disabled.
Today, simply diagnosing the stroke can eat up precious time. Patients are shuttled to a hospital where they receive an MRI or CT scan. The majority are then bundled into another ambulance and sent to a stroke center where they are seen by a specialist. Unless all that occurs within a four hour window—and often it does not—the opportunity for successful treatment expires and the damage from the stroke becomes permanent.
Living as he does in the near future, this man is luckier. An ambulance pulls up in front of his house. Rather than rushing him to the hospital for diagnosis, the EMTs slip a device that looks like a very heavy set of headphones over his head. The device uses ultrasound to measure blood flow through the man’s brain, robotics to make it easy for many to administer, and machine learning to rapidly interpret the results with higher accuracy. A diagnosis in minutes rather than hours. The EMTs pack the man who suffered a stroke into the ambulance and begin treatment on the way to the specialist.
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This scenario shows the power of democratized decisions to transform healthcare. Democratized decisions occur when data and analytics that were previously only available to specialists become available to many, many more people. These people are able to make informed decisions on topics they previously may not have touched. In some cases—if the analytics available are good enough—they may actually be able to make better decisions than the experts.
The device in the opening anecdote isn’t science fiction. It’s a product on the market today—the Lucid Robotic System, built by Neural Analytics. The Lucid System is rooted in a decades-old technology called transcranial doppler (TCD), which uses ultrasound to measure blood flow through the brain. Normally TCD is performed by human technicians, a small number of specialists who each have different techniques, introducing inconsistency and noise into the diagnosis performed by doctors who again have different interpretations.
Lucid replaces technique with technology. By deploying advanced AI and robotics, it increases consistency and boosts the signal-to-noise ratio. As a result, Lucid can distill more (and more accurate) information from TCD than was previously possible. Because every reading is captured consistently, the machine can look at small perturbations in the curve and find new signals. This new technology also democratizes access, placing diagnostic capabilities at the edge, in the hands of EMTs. That in turn enables the collection of information at sufficiently high volume to continuously improve AI-driven analysis, yielding ever greater diagnostic accuracy over time.
Democratized decisions are already on the verge of transforming how we treat strokes. But they’re also much more than that. While Neural Analytics’ Lucid system focuses on stroke, its technology can be used to diagnose other brain conditions, including traumatic brain injury. Neural Analytics isn’t creating a traditional replacement product. The system enables use not only in major medical centers, but in secondary and tertiary hospitals, small clinics, and first responders. Eventually we expect it to become ubiquitous, the same way that automatic defibrillators are available in many public spaces today. The result would be a wholesale shift in how and where key medical decisions are made.
Neural Analytics should be valued differently than a traditional medical device company. It is a data-driven opportunity anchored in the opportunity of democratized decisions to unlock new markets.
The massive increase in ability to collect, store and analyze data has enabled large tech platforms such as Google, Amazon, and Facebook to build defensibility. It also has the potential to transform new markets by putting decision-making power in the hands of the many instead of the few. Companies can change the timing, cost, location, and accuracy of decisions. They can bring transparency and efficiency to markets that are laden with opacity and friction. Ultimately they can lower the barriers to things people already want to do, causing behavioral changes that unleash latent demand, and unlock entirely new markets.
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All of this begs the question: how do new markets get unlocked? A product or service that unlocks a new market by unleashing latent demand generally does one or more of the following:
To understand how democratized decisions unlock new markets, let’s look at one of the largest sectors of our economy, housing, this time courtesy of HouseCanary.
31-year-old Carla bought her small two-bedroom house a few years ago. At the time, it was the perfect size for her. Over the last few years her family has grown, and her needs have changed. What was the perfect house is starting to feel cramped. She’s managed to save enough that she could afford a larger home. She has even identified two in her neighborhood that would make a great next step.
However, each time she thinks about moving, she is dissuaded by the enormous friction associated with multiple transactions. First, there is the time and cost needed to ready a property for sale. Second, there is the time it would take to negotiate a fair price on the new home and to sell her current home. From listing to close, each process is likely to stretch several months—on average 60 days to match a buyer and seller and then another 45 days to actually close. Third there are the transaction costs—realtors take 5-6% while another 4-5% of hidden fees are taken by intermediaries including mortgage brokers, lenders, and appraisers. Even then, once she made it through this whole process, how would she know if she got a fair price on both the home she sold and the new one she bought?
Carla is frustrated but has resigned herself that it has always been this way and is unlikely to change. This is silent suffering. “Maybe I’ll wait until next year,” she tells herself yet again.
Housing in the United States makes up 15% of GDP and is a $30 trillion asset class. Approximately $1.5 trillion worth of residential real estate trades hands each year, between buyers and sellers who have significant exposure (concentrated store of wealth) and lots of risk (heavily levered to the tune of 5-20X in most cases) yet very little information.
A large number of intermediaries were built to help consumers transact in this opaque market, but they are costly—taking in aggregate a tenth of the value of a home in fees. The consequence is inaction leading to limited mobility. As of 2016, the average homeowner lived in their house an entire decade before moving. The impact of cheap credit and lax lending standards leading up to the financial crisis proved to be temporary. Despite shifting demographics and consumer preferences, homeowner behavior has seen little change.
For decades, homeowners, buyers, and lenders who want to know what a property is worth have had to rely on an appraiser—a specialist whose assessment provides the basis for the initial transaction and the necessary validation for downstream securitization and trading of mortgage loans. This antiquated process takes a long time, uses limited data, and is inconsistent.
HouseCanary uses machines to more accurately value every property and is consequently rapidly becoming the industry standard. HouseCanary aggregates and normalizes a unique repository of data, creates new and differentiated analyses, and enables users to transact more effectively. They are democratizing this capability by bringing it from the few to the many.
Initial users sit at the top of the capital stack, providing warehouse lines and buying whole loans, and moving into the ratings agencies to securitize a loan. HouseCanary arms the global supply of capital with information to make better decisions and creates the backbone for a new approach to lending and investing in residential real estate. This is akin to what Bloomberg did for security prices, beginning with bonds—put useful, accurate, actionable data in the hands of people who previously didn’t have access to it. The second step in the democratization is to bring price transparency to 100 million homeowners and help them to make better decisions. HouseCanary is then in a unique position to link the two by pre-underwriting homes before a buyer is known. This enables a buyer to close in days, at a known value, directly to the lowest cost capital provider.
With HouseCanary, Carla will be able to behave differently. She tracks the fluctuations in the value of her home through HouseCanary’s online interface, the way people today track their stocks. She is able to make a series of decisions with better information and act on them with little friction: She can assess home value for property taxes and insurance, improve her home by investing with high return, rent her home out at market prices, and refinance it seamlessly. When Carla is ready, she puts her home on the market with the click of a button. Or perhaps the home is always for sale… for the right price. As a buyer, Carla is confident that the home she has identified is priced fairly and she can close in a matter of days.
Carla isn’t alone. The full potential for HouseCanary is built on the behavior change it inspires, the latent demand it serves, and the new markets it consequently unlocks. As HouseCanary’s solution becomes ubiquitous, time to complete a transaction will fall, and transaction costs will shrink. Homeowners will buy and sell homes more frequently, significantly increasing the size of the residential real estate market. Today, only 1% of all housing stock in the U.S. is for sale. We believe democratized decisions could cause that market to double or more in size.
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Alpha Edison seeks to understand not just what a company does today, but how it can enable behaviors to change tomorrow. Horizontal themes like democratized decisions help us to identify opportunities that redefine industry verticals.
We invest in change. Consequently, we focus on what changes will happen in the world, why they will happen, and—perhaps most importantly—when they will happen. Investing in a company ten years too early is usually worse than investing just a few years too late.
How do we know when the timing is right to invest in a democratized decision solution? Or, to put it more plainly: why do we have conviction around Neural Analytics or HouseCanary?
Sectors tend to be vulnerable to change via democratized decisions when one or more of the following conditions exists:
In medicine, only a small number of experts (specialist doctors) are able to diagnose disease, and that diagnosis often relies on their imperfect judgement. In real estate, experts (appraisers) determine home value in a similarly opaque way; they and other middlemen also charge high fees that eat up a tenth of the value of each home that changes hands. All of these are signals that those two industries are ripe for change.
Technological advancements enable democratized decisions through:
Neural Analytics takes a decades-old ultrasound technology (TCD) used to measure blood flow in the brain and combines it with robotics and AI. Robotics normalizes the data collection and removes the need for an expert with specialized skills to administer the ultrasound. Cleaner data is also richer, enabling new insights—instead of just looking at changes in the max, min, and mean values, Neural Analytics is able to derive signal from the full morphology of the TCD curve. This is fed into learning systems (AI) that make faster and more accurate diagnoses. By relying on AI instead of a specialist doctor, this system democratized decision-making, enabling non-specialists to make better decisions when it is most crucial for the patient.
HouseCanary takes in thousands of data points, some which are publicly available but exceedingly hard to aggregate and normalize, and others which are trapped in old systems such as the MLS. It then combines them with proprietary data sources which now make up over half of HouseCanary inputs. AI and image recognition is used to derive new insights from the data—condition, value, and price forecasts that are more accurate, instantly accessible, and consistently error-free. This enables better execution at scale. HouseCanary is making every property instantly searchable, financeable, and ready to transact. This new capital markets ecosystem built around HouseCanary values has network effects that build long-term defensibility. By democratizing decisions, HouseCanary unlocks a new market in residential real estate.
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The signs that a particular industry is ripe for change via democratized decisions aren’t always clear. However, with close study and attention, it is possible to see into the future, in a sense—and to use that sight to identify promising investments. Looking at a company through the lens of democratized decisions helps us understand not only the full scope of its potential impact, but the individual steps that it will take to unlock that impact over time. In the cases of HouseCanary and Neural Analytics, it gives us conviction that there is a pathway to enormous returns—and potential to improve outcomes and ease suffering for millions of people.